Mammalian whiskers have attracted increasing interest from engineers seeking to imitate their numerous desirable sensing properties. Whiskers are physically robust, mechanically simple, and yet can precisely extract object shape, texture and the velocity of fluid flow. The diverse capabilities of whiskers are amply demonstrated by the animals that use them to perform difficult behavioral tasks; for example, seals can track hydrodynamic trails [1] and rats can distinguish small differences in aperture width [2]. Robotic whiskers have been used for various types of sensing tasks (for a detailed review, see [3]), and several recent studies have specifically addressed the issue of three-dimensional (3D) feature extraction, wherein the goal is to infer the shape of an object by repeated contact with one or more whiskers. These studies have generally taken one of two approaches: whisker “tapping” or whisker “sweeping.”
The first approach—whisker tapping—is to rotate or translate the whisker(s) against an object by a small angle and infer where along the length of the whisker initial contact occurred (radial distance extraction). Using this information, along with information about the angle of initial contact and location of the whisker base, allows estimation of the contact point location in 3D space for each whisker/whisk.
Whisker tapping has been relatively well studied. Tsujimura and Yabuta derived and demonstrated a general method of estimating contact point location of a stiff probe pressing against an object using a six-axis force/torque sensor [4]. Ueno et al. measured vibration frequencies at the base of a flexible beam using a torque sensor to estimate contact point position [5]. Kaneko et al. used a two-axis actuator, two-axis torque sensor and a flexible beam to determine contact positions along an object based on the rotational compliance [6]. Clements and Rahn applied a large angle elastica model as the basis for determining contact point location with a two-axis actuator, flexible beam and six-axis force/torque sensor [7]. Kim and Möller attached multiple flexible beams with two-axis torque sensors to an actuated support plate, showing that whisker arrays can provide basic object shape information in a single whisk [8]. Detailed shape information can be extracted by using a whisker array and combining data from several whisks and accounting for lateral slip of the whiskers along the object [3, 9].
The second approach—whisker sweeping—involves moving the whisker along or against the object far past the location of initial contact in order to estimate a collection of contact point locations as the whisker slips along the surface. Whisker sweeping has received less attention in the literature than tapping. Russell swept the tip of a flexible curved beam with a binary (touch or no-touch) sensor along objects with a Puma robot to measure their profile [10]. Wilson and Chen used a pneumatic bellow tube actuation system and closed-loop control to sweep the tip of a flexible beam with a 2D torque sensor along objects and estimate their profiles [11]. Scholz & Rahn rotated a flexible beam equipped with a six-axis force/torque load cell against objects and used a large-angle elastica model to repeatedly compute the entire whisker shape and contact point, providing an accurate 2D object profile measurement with a single whisk [12]. Critical differences between this method and that of the present invention will become apparent.